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Enkrypt AI MCP Server

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retrieve_policy_configuration

Retrieve policy configuration details by specifying the policy name, enabling access to structured policy data for analysis and implementation.

Instructions

Retrieve and print the policy configuration for a given policy name.

Args: policy_name: The name of the policy to retrieve.

Returns: A dictionary containing the policy configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
policy_nameYes

Implementation Reference

  • The handler function for the 'retrieve_policy_configuration' tool, decorated with @mcp.tool() for registration. It retrieves the policy using guardrails_client.get_policy and returns a dictionary with policy details, name, and detectors.
    @mcp.tool()
    def retrieve_policy_configuration(policy_name: str) -> Dict[str, Any]:
        """
        Retrieve and print the policy configuration for a given policy name.
    
        Args:
            policy_name: The name of the policy to retrieve.
    
        Returns:
            A dictionary containing the policy configuration.
        """
        policy = guardrails_client.get_policy(policy_name=policy_name)
    
        # Return policy details as a dictionary
        return {
            "policy": policy.to_dict(),
            "name": policy.name,
            "detectors": policy.detectors.to_dict()
        }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'retrieve and print' but doesn't specify whether this is a read-only operation, what permissions are required, how errors are handled, or if there are rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by brief sections for arguments and returns. Every sentence earns its place without redundancy, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally complete. It covers the basic purpose and parameter but lacks details on behavior, error handling, and differentiation from siblings, which are important for full contextual understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal semantics beyond the input schema: it explains that 'policy_name' is 'the name of the policy to retrieve,' which clarifies the parameter's purpose. However, with 0% schema description coverage and only one parameter, this is adequate but not comprehensive—it doesn't detail format constraints or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('retrieve and print') and resource ('policy configuration'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_guardrails_policy' or 'use_policy_to_detect', which appear to be related to policy operations, so it doesn't fully distinguish itself from alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_guardrails_policy' and 'use_policy_to_detect' that might overlap in functionality, there's no indication of context, prerequisites, or exclusions for using this specific retrieval tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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